Our common heritage is a central element of our communities and economies, and a principal but vulnerable dimension of our common identity as Europeans. It has been proven that cultural heritage contributes to well-being, social cohesion, identity, local economy, territorial attractiveness, and environmental sustainability, but the climate crisis and natural hazards endanger this heritage. We propose RescueME to take immediate action for demonstrating how an innovative data-driven, community-based, heritage-centric actionable landscape approach to resilience enhancement can protect our cultural heritage and landscapes while supporting the transition toward a green society and economy that sustains resilient, cohesive, nature-connected communities. RescueME proposes a call for action, broadening the scope, triggering action, untapping and mobilizing resources, engaging actors, and facilitating the decision making and the implantation of co-created just resilience solutions to protect our common heritage. RescueME will develop, test and demonstrate the effectiveness of an Actionable Framework based on the Resilient Historical Landscape approach (RHL) complemented by data, models, methods, and tools able to assess risks and opportunities, co-develop inclusive and just resilience strategies and innovative solutions to protect European cultural heritage and cultural landscapes from climate change, disaster risk, as well as other stressors (such as pollution and over-tourism) with special focus on European coastal landscapes since a large share of this endangered heritage there. The five case studies (Psiloritis in Creta, Neuwerk in Hamburg, Portovenere, Cinque Terre & the Islands, València and the city of Zadar) have been selected carefully as complementary representatives of European coastal landscapes. They will act as resilience landscape laboratories (R- labscapes), validate the results and ensure their replicability.

DESIRA will develop the concept of Socio-Cyber-Physical Systems to advance understanding of the impact of digitisation in rural areas, linking analysis directly to the United Nation’s Sustainable Development Goals. Operationalising the Responsible Research and Innovation approach, DESIRA will enrol agriculture, forestry and rural stakeholders in co-developing scenarios and policies in Living Labs established in 20 European Regions, and a Rural Digitization Forum gathering 250 stakeholders from all Europe. A Virtual Research Environment tailored to the purposes of the project will connect all participants and allow to increase substantially the interaction within the network. DESIRA will provide a Taxonomy and Inventory of Digital Game changers which will be implemented into an online Visualization Tool, a Set of Socio-Economic Impact Indicators aligned to the Sustainability Development Goals implemented into an online Socio-Economic Impact Tool, a Pan-European Assessment of digitization in European rural regions, a Needs, Expectations and Impact appraisal report, a Comparative Scenario Report based on scenario development activities of Living Labs and the Rural Digitization Forum, a Policy analysis and Roadmap, an Ethical Code to be adopted by researchers and innovators and recommended by policy bodies, five Use Cases that will report a further analysis – co-created by Living Labs with the support of ICT specialists - of the most promising solutions identified by Living Labs, Showcase Technologies - including a Virtual Farm Platform - that will create a selection of proof of concepts suggested by Use Cases. A detailed, multi-media dissemination, engagement and communication strategy will accompany the project from the beginning, looking at research as a multifunctional (research, engagement and communication) process and at the same time involving communication specialists in the development of adequate messages and in the choice of the most effective media.

Foundation models represent a paradigm shift in AI, exhibiting remarkable capabilities across multiple tasks. Their true potential lies in generalizing across diverse domains and modalities, a largely untapped frontier. DVPS advances this frontier by focusing on multimodal foundation models (MMFM), aiming to harness their capabilities across various application domains. DVPS emphasizes three core benefits of MMFM: label efficiency, compute reusability, and engineering efficiency. However, achieving these benefits in multimodal settings presents challenges such as modality-specific architecture and cross-modal alignment. To overcome these, DVPS aims to develop generalizable methods that work across diverse modalities and domains, creating a unified framework for MMFM development and integrating new modalities into existing models. The project focuses on generating foundational knowledge, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. DVPS also includes two "surprise domains" to drive innovation by challenging initial assumptions. Key objectives include the development of AutoDVPS, a toolkit for automated MMFM design, and the creation of DVPSBench, a benchmarking suite for evaluating MMFM across tasks and domains. DVPS aims to foster a European ecosystem for MMFM research, promoting transparency, fairness, and ethical compliance in line with European values. Through collaboration and open-source contributions, DVPS seeks to standardize and advance MMFM as a scientifically rigorous discipline.

Earth system models (ESM) show diverging estimates of ecosystem carbon (C) uptake which drives persistent uncertainty about future climate and limits the realization of policy mitigation goals. The CONCERTO project aims to strengthen the European research ecosystem by creating an innovative scientific collaborative framework that enhances our understanding, monitoring, and modelling of the terrestrial cycle (CC), and leads to reduced uncertainty and ESM convergence. This framework has three main elements: the exploitation of novel Earth Observation (EO) data, the innovation of process models fed by these data, and Data Assimilation (DA) and Machine Learning (ML) techniques. The consortium includes European experts and institutes active in these areas. CONCERTO will advance the representation of land cover, leaf area index (LAI) and management intensity through new maps of high resolution with layers relevant for the CC. The new management map will enhance the creation of a new biomass production map. Further, CONCERTO will prepare for the ingestion of FLEX data in land surface models (LSM) through DA, and exploit Sentinel-5P/TROPOMI HCHO indicative of biogenic volatile organic compound (VOC) emissions. As step towards moving away from prior (static) parameterizations, the novel P model will be used to ingest these new data sources. This will enhance understanding of ecosystems responses to climate extremes, fires, and vegetation recovery from them, and the parameterization of LSMs included in ESMs. Novel representations of the underrepresented processes of lateral carbon fluxes through outgassing of CO2 from rivers will be developed. Dedicated seasonal and climate experiments will demonstrate how improved representation of land surface processes benefit the accuracy and trustworthiness of global Earth System simulation. This will lead to better predictability of the influence of land management on the CC and underpin avenues towards carbon neutrality

A vast amount of Earth Observation data is produced daily and made available through online services and repositories. Contemporary and historical data can be retrieved and used to power existing applications, to foster innovation and finally improve the EU citizens’ lives. However, an undersizedaudience follows this activity, leaving huge volumes of valuable information unexploited. EO4EU aims to provide innovative tools, methodologies and approaches that would assist a wide spectrum of users, from domain experts and professionals to simple citizens to benefit from EO data. EO4EU strives to deliver dynamic data mapping and labelling based on AI adding FAIRness to the system and data. EO4EU introduces an ecosystem for holistic management of EO data, bridging the gap among domain experts and end users, bringing in the foreground technological advances to address the market straightness towards a wider usage of EO data. EO4EU envisages to boost the Earth Observation data market, providing a digestible data information modeling for a wide range of EO data, through dynamic data annotation and a state-of-the-art serverless processing by leveraging important European Cloud & HPC infrastructures.